Radar can be used to detect and track targets in a radar scene. Systems for such detecting and tracking can transmit an RF signal onto a radar scene and receive the reflected RF signal from targets and clutter. A common detection technique is homodyne detection. The received signal can then be processed, for example, via digital signal processing (DSP), after amplification and/or filtering, to provide data for detection and tracking of objects in the radar scene.
Radar systems can suffer from amplitude modulation (AM), which can be referred to as AM noise, on the received signal. Reduction of the AM noise can improve the performance of the radar system.
In radar systems for detecting and tracking targets, it can be important to quickly obtain meaningful detection and tracking information as quickly as possible after turning the system on. For example, there can be situations where the system is turned on only when a user determines a potential target may be in the radar scene. In this case, it is often advantageous to have the system provide detection and tracking to the user soon after turning the system on. Typical systems can incorporate a digital comb filter for adapting to the AM noise in order to reduce the AM noise. Such digital comb filters can take on the order of ten seconds to adapt to the AM noise signal and thus delay the system from providing the user meaningful detection and tracking information. It would be advantageous if the digital comb filter could adapt to the AM noise quicker.
A primary objective of a radar sensor is to maximize detection while simultaneously minimizing false alarms. Many radar sensors create range-Doppler maps (RDMs) in which the amplitude values of each cell represent potential target detects. When no targets are present in the sensor environment, the amplitude values in each cell are proportional to the noise and clutter background detected by the radar. What targets are present in the radar environment, these may appear in the cells of the range-Doppler map with somewhat larger amplitude, depending on the target size, distance from the radar and other factors. A radar system may utilize a digital signal processor (DSP) to perform the necessary signal processing tasks to create the RDM. This signal processing may be performed with fast Fourier transform (FFT) techniques or other techniques. In radar systems employing DSPs, computational power and memory may be limited.
Techniques to process the information in range-Doppler maps more efficiently and to provide data relevant to detection and tracking can improve the performance of radar systems for detection and tracking, for a given amount of computational power and memory.
Once a target is detected and/or tracked, it can be valuable to provide information to the user as to what type, or class, of target it is. Providing information as to the class of the target is often referred to as classification. A particular distinction that can be useful is to determine whether a target is a human being or a truck. Techniques for processing data obtained from a received RF signal in the radar system to provide more accurate classification of targets, for a given computational power and memory, can be valuable to the user.